Background Food material science has evolved to support the development of food products
by connecting food structure, sensory, nutrition, food processing, and digestion with impact …

REINVENT 4 is a modern open-source generative AI framework for the design of small
molecules. The software utilizes recurrent neural networks and transformer architectures to …

Generative adversarial networks (GANs) have recently attracted attention owing to their
impressive ability in generating high-quality and novel synthetic datasets such as signals …

A high-performance tire X-ray defect image classification method plays a key role in
enhancing the automation level of tire defect detection. In industrial practice, however, a …

The utility of machine learning (ML) techniques in materials science has accelerated
materials design and discovery. However, the accuracy of ML models-particularly deep …

Lattice structures have been a hot topic recently owing to their superior mechanical
properties, which are significantly influenced by the unit cell structure. By leveraging the …

Generative adversarial networks (GANs), as a powerful tool for inverse materials discovery,
are being increasingly applied in various fields of materials science. This review provides …

Existing fashion recommendation systems encounter difficulties in using visual data for
accurate and personalized recommendations. This research describes an innovative end-to …

The conventional approach to achieve desired effective thermal conductivity (ETC) of porous
thermal interface materials (TIM) is processing-microstructure-properties forward analysis …

The efficient search for crystals with targeted properties is a significant challenge in
materials discovery. The rapidly growing field of materials informatics has so far primarily …